Tango answers questions from a sabermetric skeptic

The above quote illustrates why I enjoy Tango’s work. Everyone has an opinion — what’s the old saying? — and they’re entitled to that. But that doesn’t mean we should take every opinion seriously. Only opinions backed by argument, based on facts and a logical thought process, warrant consideration. So when a fairly prominent blogger tries to stir the pot by deriding the sabermetric community, using little or no evidence, Tango will likely respond.

We’re no strangers to Mike Silva. We’ve addressed at least one of his evidence-less rants, and see plenty more of him on the BBTF Newsstand. In the traditional talk radio style, he makes emotional appeals as a substitute for evidence, but that type of argument doesn’t fly in statistically inclined baseball communities. We require evidence.

Proving that he’s not 100 percent gasbag, Silva agreed to send Tango 10 questions about advanced statistics and the sabermetric community. Before linking to the entire series, I’d like to note some highlights.

My biggest beef with Silva — the reason I no longer visit his site — is his stance on the sabermetric community. He suggests that “the ultimate goal is to mainstream their theories and perhaps gain more power in the baseball community.” Using “mainstream” as an infinitive peeves me enough, but the idea that statistically inclined fans want to gain more power is preposterous. Tango rightfully takes Silva to task on this issue, though his focus is more on the second part of Silva’s non-question, wherein he claims that “the ‘value’ of hose these metrics can be used seems to be marginal in my opinion.” Tango:

It’s one thing to say that you don’t understand it, so either you accept it or want to learn more or ignore it. It’s another thing to say that you don’t understand it, and so you will dismiss it as being “marginal” or worse. You have no basis for dismissal. Ignore it, if you must. Dismissing it is out of the question. There’s a huge number of people that find value in it.

Another interesting sequence arises when Silva asks about the future of sabermetrics. Where will we see advanced metrics in 10 years? “Fad? Major part of a front office operation? Replace traditional scouting?” No, yes, and no are the correct answers, but Tango takes it a step further.

You haven’t seen anything yet. Wait until PITCHf/x, FIELDf/x, and HITf/x take shape. You will wish and pray to get back to the simpler times of 2000s. The 2010s will bring an avalanche of data. It will absolutely be a major part of the front office. The best-case scenario is that you have all these f/x systems set up at colleges and high schools. Instead of one scout seeing one game of some prospect in one town, while missing a game on another town, you will have every single pitch charted, every swing charted, and every single fielder charted. The question is to try to identify all of the contributions of each player to each pitch and each play. Having a summary opinion without evidence is bullsh!t. Scouts have summary opinion on limited amount of data (say they see 5% of someone’s games in college). That’s valuable. Now, imagine having a summary opinion based on 100% of the data?

I also enjoyed Tango’s explanation of FIP. I think this point is lost on many proponents of the stat: “it is only concerned with one component to pitching. And that component is the one that does not involve his fielders.” It’s like OBP, and Tango makes that connection as well. It tells us just one thing. It happens to be a very important thing, but there are other factors to consider, just as we consider factors like power and base hits when discussing OBP.

If you have questions about sabermetrics yourself, or you just want to see Tango dole out some quality arguments and explanations, I recommend the entire series. It’s not an overly long read, and I think it’s totally worth the time.

I’m 200 pages into Moneyball. Billy Beane and Paul Depodesta (assistant GM) were quite something in their respective hey-days. Not sure if this post is off-topic, but I wonder how much different baseball would look … how much different would the Yankees look … if Beane and Depodesta didn’t implement this valuation system.

Bo

Just because Beane was part of the book doesnt mean he and the A’s were the only ones implenting that value system.

For example look at what Stick Michael did with the Yankees in the early 90’s.

I agree… Beane/DePo and the rest of the guys with the A’s back then certainly were in the forefront of this stuff, as far as MLB front offices are concerned, but they didn’t create sabermetrics and they’re not responsible (nor is Lewis’s book) for the proliferation of advanced analysis in MLB. It’s simply a matter of progress. They, and the book, may have helped popularize the progress, but it was happening, and would have continued to happen, without that book and without the Beane/DePo crew.

Michael Kay

This is the silliest war in sports. Two sides who get their panties in a bunch over the other side’s refusal to accept their opinion. Please don’t get politics in my sports and I’ll keep my sports out of your politics. If it doesn’t stop we’ll turn on MLB Network someday and see S (Sabermetricat) and T (Traditionican) next to analysts names.

Sabermetrics will be used my those who see their merit & value, if a portion of the population doesn’t see value in them, who cares? They don’t become any less telling of statistics just because some stodgy old baseball writers & MLB personnel don’t use them. Its actually more irritating than watching fans of two different teams try to convince each other they are somehow foolish for cheering for their perspective team.

Tampa Yankee

The point of this post

————————-

Your head

Michael Kay

were you just waiting for any post to use this line? Because clearly you didn’t actually read mine.

Tampa Yankee

Actually I wasn’t and yes I did.

This is the silliest war in sports. Two sides who get their panties in a bunch over the other side’s refusal to accept their opinion

Neither Tango or Joe are arguing that the only way to evaluate players value is to use Sabermetrics and that traditional scouting of players is old and archaic. But that’s what it seems you are suggesting by that line.

Its actually more irritating than watching fans of two different teams try to convince each other they are somehow foolish for cheering for their perspective team.

Who is arguing it’s one or the other? Who is stating that the other is foolish other than Silva? Both Tango and Joe seem to be saying that there is value in both ways. As technology advances there are more and more ways to evaluate players but that doesn’t mean traditional scouting is out the window.

Michael Kay

and where did I use their names indicating I said they were arguing about it? I commented on a general topic related to the discussion. Thanks.

“Sabermetrics will be used my those who see their merit & value, if a portion of the population doesn’t see value in them, who cares?”

I care, because I don’t respect the opinions of people who don’t understand the value/utility of statistical analysis. If two people have different opinions about the value of a certain player or strategy or anything at all, really, and one has evidence on his side and the other eschews the very concept of trying to gather such evidence, why would you put any credence at all into the opinions of the latter person? This isn’t a baseball thing, it holds true in any walk of life.

“They don’t become any less telling of statistics just because some stodgy old baseball writers & MLB personnel don’t use them.”

First of all, I’m sorry, but I’m not quite sure what this sentence means… Poor writing aside, though, I think you’re trying to say that people who appreciate statistical analysis don’t have to be sensitive about “stodgy old baseball writers & MLB personnel” dismissing such statistical analysis. But you’re creating a fantasy conflict that doesn’t actually exist. This isn’t a geeks vs. jocks argument, as it’s often made out to be. I don’t care if the person dismissing statistical analysis is a stodgy old man or a 22 year old kid in his mother’s basement, he’s wrong either way.

pat

I’m not gonna lie I got a little excited when he mentioned FIELDf/x, and HITf/x.

Andy in Sunny Daytona

What’s the difference between a line drive and a fly ball? Are defensive zones an imaginary area based on where a fielder is traditionally placed or is where the fielder is positioned when the ball is put in play?

The lines between them are fuzzy, and obviously it’s a judgment call made on the spot.

ColoYank

The list of top FIP and ERA leaders put me on the fence. The two rankings are so nearly identical – what new fact did the FIP give you about comparative values of pitchers?

And I think that’s one thing that the stodgy old stats have in common with the new-fangled stats: they’re good for comparing players to each other and, for an individual player, comparing time periods one against the other. (There is one other feature they share: they’re both subservient to the one stat that counts: winning percentage.)

I don’t profess to understand most of the new stats, except they seem conducive to looking more closely at isolated details of performance abilities and trends.

The Fallen Phoenix

Predictive power. There is a higher correlation between a good FIP and good ERAs in the future than there is between a good ERA and good ERAs in the future.

Put simply, statistics, as a discipline, is all about building models that allow you to use limited data in order to determine what components contribute the most to observed events, in order to best predict how events might unfold in the future.

Steve H

Agreed, much like the Pythag for teams, it does a good job of telliong who was lucky and unlucky, but it doesn’t change the results. If two teams have 95 win pythags, but one wins 88 games and one wins 102, the 102 win team was better that season. If the same two teams played 162 more games, they’d like head more towards the norm.

Same with FIP, if two guys have identical FIPS, but one has an ERA of 3.00 and the other has an ERA of 4.00, the guy with the lower ERA had a better season, though he didn’t necessarily pitch better. To a point, I could care less what Sabathia’s FIP is this year, but I certainly care about his ERA. However, when looking at a free agent/trade possibility, FIP would weight much more heavily, or if a guy like Sabathia, while maintaining similar ERA had a rising FIP, I would be concerned.

ColoYank

Okay. That’s helpful, guys, thanks.

toad

they’re both subservient to the one stat that counts: winning percentage.)

That’s the main thing.

This whole argument seems foolish to me. There’s an easy way to settle it, at least in the abstract. Do sabermetrics do a better job of predicting who is going to win than the more traditional stats? If not, they are a waste of time. If so, then use them.

Everybody uses statistics. The only thing special about batting average, RBI’s, etc. is that they were first compiled a long time ago. If you’re going to say X is better than Y because he has a higher batting average, despite having a lower OPS, you have to explain why batting average is a better measure of a player’s contribution to winning. (The OPS advocate has the opposite problem, of course). That batting average is older doesn’t count.

Rich

How bout we just stop playing the actual game on the field….and instead play on our computers?

Or how about the people who make the important decisions use predictive data (with the help of computers) to put the best team on the field as possible.

Steve H

Let’s ban women from voting too. And allow smoking in schools. And pregnant women should drink and smoke at will. And who needs seatbelts. And the internet, let’s get rid of it.

Progress is clearly overrated.

Rich

What do you mean?

i am progressing…I’m taking ANY POSSIBLE human element out of the game and putting it into the hands of computers who will soon rule the world. thats progress at the highest level, my fiend.

ColoYank

I for one welcome our new computer overlords.

Bo

Front offices have been using stats and saber type theories since baseball started. It isn’t new.

Mr.Jigginz

I disagree…I’ve seen too many people treat sabermetrics as something new,and since I saw them with my own eyes,it must be true…UCWIDT?

http://jukeofurl.wordpress.com Juke Early

The implementation & acceptance of the “new” stats can help a franchise put the best team on the field. It is however from a “field” of diminishing returns. Oddly, unlike most computer based innovations, rather than eliminating jobs, it creates some more. You gotta like that deal.

And yet when your choice is say Jerry Hairston as your everyday LF or your bench player over Brett Gardner, do the numbers make your decision for you – or do you go with your gut? Or do you sign Matt Holliday for 3 more Ws(?). How many wins do each player on each team guarantee based on these predictors? do they add up? To what? Debates, I think.

I don’t think Mike Silva or any savvy observer of baseball dismisses anything 100%. Most of us like stats. But the one and only fact is the one most of you neglect to address, they are based on the past. If they could accurately predict performance, why play the games? Well, for the money, natch.

Can they tell you Bucky Dent hits that HR v. Mike Torres? or that Alex Rodriguez was juicing? The narrow focus of most sports people, while logical & pragmatic, is a weakness. You can rip anyone at anytime for having a dissenting opinion, it made America famous. But just like the US & the world’s state now, these new stats just dig a deeper hole. While you, if you’re lucky, get paid to see what crawls out. What’s not to like, huh?

“But the one and only fact is the one most of you neglect to address, they are based on the past. If they could accurately predict performance, why play the games?”

In order for this statement to make sense, the people on the other side of the argument would have to be arguing that there’s no need to play the games on the field because we can create statistical models to predict the future. The problem, of course, is that nobody is saying anything remotely close to that. Nobody’s neglecting to address that point, it’s just irrelevant.

pete

Baseball isn’t football though. They don’t play 16 games a season, have 50+ players on the team, red shirt draftees for half a season before playing them in the Show. Baseball is played out over such an extended sample that it’s data actually does generate predictive power. Of course a lot of unpredictable noise can affect the play on the field, but baseball, like any sport, is a business, and the best way to succeed as a business in baseball, long term, is to win. And the best way to build a team that wins is through a careful amalgamation of available data.

It’s not exactly the same in other sports (though I expect basketball to make significant sabermetric advances soon), because in baseball there are so many traceable data points. If you (rightly) consider each pitch a mappable event, then you have about 150 events per team per game. Since each team plays 162 games each year, that means you have about 24300 data points per season. When this much data stacks up, why wouldn’t people, especially those in charge of churning out winning teams, try to find things that correlate to winning, and how strong those correlations are?